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This role is responsible for driving advanced analytics, AI, and machine learning solutions to improve Supply Chain performance and decision-making. The individual will work as a self-starter, translating complex business challenges across planning, procurement, inventory, manufacturing, and customer fulfillment into scalable analytical solutions. They will design, develop, and deploy diagnostic, predictive, and prescriptive models, while collaborating with global cross-functional stakeholders across business, analytics, and technology teams. The role also involves rapidly building AI-powered prototypes and MVPs, leveraging Supply Chain expertise, data science, and emerging technologies to convert data into actionable insights and business value, while owning solutions end-to-end from ideation through adoption.

Roles & Responsibility:

• Analyze Supply Chain KPIs to identify trends, risks, opportunities and root causes.
• Design complex and optimized SQL solutions across large and multiple data sources.
• Build scalable datasets and analytical solutions using Databricks, SQL, Python and enterprise data platforms.
• Build end-to-end analytical applications, including data, business logic, backend/API and user interface.
• Develop rapid prototypes and MVPs for new Analytics, AI and Supply Chain ideas.
• Design and develop Machine Learning solutions for forecasting, prediction, anomaly detection and optimization.
• Build GenAI/LLM solutions using prompt engineering, RAG, APIs and enterprise data.
• Develop prescriptive solutions that recommend actions based on business conditions and constraints.
• Translate ambiguous business problems into structured analytical and technical solutions.
• Work with complex and fragmented enterprise data from SAP/ERP and other operational systems.
• Develop executive-level insights and recommendations for business decision-making.
• Own solutions from problem definition through design, development, testing, deployment and value realization.
• Work with IT and Data Engineering teams to transition MVPs into scalable production solutions.
• Continuously evaluate emerging AI, ML and analytics technologies for Supply Chain applications.

Desired Candidate Profile:

• 6–8 years of experience in Data Science, Advanced Analytics, AI/ML, Analytics Engineering or Supply Chain Analytics.
• Strong hands-on experience solving complex Supply Chain analytics problems independently.
• Experience in automotive, manufacturing or Supply Chain environments preferred.
• Experience across planning, procurement, inventory, manufacturing, customer fulfillment use cases.
• Demonstrated experience developing analytical applications, prototypes, proof-of-concepts and MVPs.
• Demonstrated experience delivering Analytics/AI solutions from business problem through production deployment.

PROFESSIONAL EXPERIENCE:

• Strong hands-on expertise in SQL, Python, Databricks, Power BI and modern AI/ML technologies.
• Strong ability to design complex SQL queries and work with large, complex and multi-source datasets.
• Hands-on experience with Databricks, Spark/PySpark, Delta Lake and Lakehouse architecture preferred.
• Strong hands-on experience developing Machine Learning and Data Science solutions using Python.
• Experience with regression, classification, clustering, forecasting, anomaly detection and optimization techniques.
• Experience with feature engineering, model training, validation, evaluation and explainability.
• Experience developing GenAI/LLM solutions using prompt engineering, RAG, APIs and structured outputs.
• Experience building data and AI applications using Python-based application frameworks.
• Experience developing and integrating REST APIs, backend logic and database connections.
• Understanding of AI/ML deployment, monitoring, MLOps and productionization concepts.
• Strong understanding of end-to-end Supply Chain processes, constraints and performance drivers.
• Ability to translate Supply Chain processes into analytical, statistical and optimization logic.
• Experience with demand, supply, inventory, safety stock, MOQ, lead time, BOM and service-level analytics.
• Experience integrating data from SAP/ERP, CRM, WMS/TMS and other enterprise systems.
• Strong understanding of data quality, governance, security, reconciliation and lineage.
• Ability to independently troubleshoot complex data, application and model-related problems.
• Ability to convert ambiguous business challenges into structured solutions, user stories and technical requirements.
• Experience managing analytics and AI projects end-to-end from ideation through deployment and adoption.

SPECIAL QUALIFICATIONS/ SKILLS:

• Strong understanding of end-to-end Supply Chain processes and KPIs.
• Strong analytical, technical and problem-solving capabilities.
• Strong SQL, Python, Data Science and AI/ML capabilities.
• Strong technical understanding of Databricks and modern data architectures.
• Ability to independently design and build complex analytical and AI solutions.
• Ability to rapidly convert ideas into working prototypes and MVPs.
• Strong consulting mindset with focus on measurable business value.
• Strong stakeholder management and communication skills.
• Ability to simplify complex technical concepts for business leaders.
• Ability to work independently with limited supervision in a global environment.
• Knowledge of AI governance, data privacy and responsible AI practices.
• Strong curiosity and ability to quickly learn new technologies and business domains.
  

EDUCATION/KNOWLEDGE:

• Bachelor’s or master’s degree in engineering, Computer Science, Statistics, Data Analytics, Supply Chain, Operations, or a related field.
• Advanced qualification or certification in Data Science, AI/ML, Analytics, Cloud or Supply Chain is an advantage.

Competencies

ABOUT TE CONNECTIVITY

TE Connectivity plc (NYSE: TEL) is a global industrial technology leader creating a safer, sustainable, productive, and connected future. As a trusted innovation partner, our broad range of connectivity and sensor solutions enable the distribution of power, signal and data to advance next-generation transportation, energy networks, automated factories, data centers enabling artificial intelligence, and more.

Our more than 90,000 employees, including 10,000 engineers, work alongside customers in approximately 130 countries. In a world that is racing ahead, TE ensures that EVERY CONNECTION COUNTS. Learn more at www.te.com and on LinkedIn, Facebook, WeChat, Instagram and X (formerly Twitter).

WHAT TE CONNECTIVITY OFFERS:
We are pleased to offer you an exciting total package that can also be flexibly adapted to changing life situations - the well-being of our employees is our top priority!

• Competitive Salary Package
• Performance-Based Bonus Plans
• Health and Wellness Incentives
• Employee Stock Purchase Program
• Community Outreach Programs / Charity Events
• Employee Resource Group

IMPORTANT NOTICE REGARDING RECRUITMENT FRAUD
TE Connectivity has become aware of fraudulent recruitment activities being conducted by individuals or organizations falsely claiming to represent TE Connectivity. Please be advised that TE Connectivity never requests payment or fees from job applicants at any stage of the recruitment process. All legitimate job openings are posted exclusively on our official careers website at te.com/careers, and all email communications from our recruitment team will come only from actual email addresses ending in @te.com. If you receive any suspicious communications, we strongly advise you not to engage or provide any personal information, and to report the incident to your local authorities.

Across our global sites and business units, we put together packages of benefits that are either supported by TE itself or provided by external service providers. In principle, the benefits offered can vary from site to site.

Job Locations:

Doraisanipalya, J.P Nagar, 4th Phase, Bannerghatta Road
Bangalore, Karnātaka 560076
India

Posting City: Bangalore

Job Country: India

Travel Required: Less than 10%

Requisition ID: 157282

Workplace Type: Hybrid

External Careers Page: Information Technology